Integration of beamforming and uncertainty-of-observation techniques for robust ASR in multi-source environments

Computer Speech and Language

Volumn 27, Issue 3, 2013, Pages 837-850

  Astudillo, Ramón Fernandez ^a   Kolossa, Dorothea ^b   Abad, Alberto ^a   Zeiler, Steffen ^b   Saeidi, Rahim ^c   Mowlaee, Pejman ^b   Da Silva Neto, João Paulo ^a   Martin, Rainer ^b  

^a INESC ID   (Portugal)

^b RUHR UNIVERSITY BOCHUM   (Germany)

^c RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

Author keywords

Beamforming; Robust speech recognition; Uncertainty decoding; Uncertainty propagation

Indexed keywords

BEAMFORMING; DECODING; SIGNAL PROCESSING; UNCERTAINTY ANALYSIS;

AUTOMATIC SPEECH RECOGNITION; DELAY-AND-SUM BEAMFORMERS; MULTI-CHANNEL SIGNAL PROCESSING; OBSERVATION UNCERTAINTIES; ROBUST SPEECH RECOGNITION; UNCERTAINTY DECODING; UNCERTAINTY PROPAGATION; UNCERTAINTY-OF- OBSERVATION TECHNIQUES;

SPEECH RECOGNITION;

EID: 84893328634     PISSN: 08852308     EISSN: 10958363     Source Type: Journal    
DOI: 10.1016/j.csl.2012.07.009     Document Type: Article

References (39)

1. Astudillo, R.F., 2010. Integration of Short-Time Fourier Domain Speech Enhancement and Observation Uncertainty Techniques for Robust Automatic Speech Recognition. Ph.D. Thesis. Technical University Berlin.
2. R.F. Astudillo, A. Abad, and J.P. Neto Integration of beamforming and automatic speech recognition through propagation of the Wiener posterior Proc. ICASSP 2012 4909 4912
3. R.F. Astudillo, D. Kolossa, P. Mandelartz, and R. Orglmeister An uncertainty propagation approach to robust ASR using the ETSI advanced front-end IEEE JSTSP Special Issue on Speech Processing for Natural Interaction with Intelligent Environments 4 2010 824 833
4. R.F. Astudillo, D. Kolossa, and R. Orglmeister Uncertainty propagation for speech recognition using RASTA features in highly nonstationary noisy environments ITG Workshop for Speech Communication 2008
5. R.F. Astudillo, D. Kolossa, and R. Orglmeister Accounting for the uncertainty of speech estimates in the complex domain for minimum mean square error speech enhancement Proc. Interspeech 2009 2491 2494
6. R.F. Astudillo, and J.P. Neto Propagation of uncertainty through multilayer perceptrons for robust automatic speech recognition Proc. Interspeech 2011 461 464
7. R.F. Astudillo, and R. Orglmeister A MMSE estimator in mel-cepstral domain for robust large vocabulary automatic speech recognition using uncertainty propagation Proc. Interspeech 2010 713 716
8. J. Barker, E. Vincent, N. Ma, H. Christensen, and P. Green "The PASCAL CHiME Speech Separation and Recognition Challenge" Computer Speech and Language 27 3 2013 621 633
9. M. Brandstein, and D. Ward Microphone Arrays: Signal Processing Techniques and Applications 2001 Springer
10. I. Cohen Noise spectrum estimation in adverse environments: improved minima controlled recursive averaging IEEE Transactions on Speech and Audio Processing 11 2003 466 475
11. M. Cooke, J. Barker, S. Cunningham, and X. Shao An audio-visual corpus for speech perception and automatic speech recognition Journal of the Acoustical Society of America 120 2006 2421 2424
12. M. Delcroix, K. Kinoshita, T. Nakatani, S. Araki, A. Ogawa, T. Hori, S. Watanabe, M. Fujimoto, T. Yoshioka, T. Oba, Y. Kubo, M. Souden, S.J. Hahm, and A. Nakamura Speech recognition in the presence of highly non-stationary noise based on spatial, spectral and temporal speech/noise modeling combined with dynamic variance adaptation International Workshop on Machine Listening in Multisource Environments (CHiME 2011) 2011 12 17
13. L. Deng Front-end, back-end, and hybrid techniques to noise-robust speech recognition D. Kolossa, R. Haeb-Umbach, Robust Speech Recognition of Uncertain or Missing Data - Theory and Applications 2011 Springer Berlin, Germany 67 99 (Chapter 4)
14. L. Deng, J. Droppo, and A. Acero Exploiting variances in robust feature extraction based on a parametric model of speech distortion Proc. International Conference on Spoken Language Processing 2002 2449 2452
15. L. Deng, J. Droppo, and A. Acero Dynamic compensation of HMM variances using the feature enhancement uncertainty computed from a parametric model of speech distortion IEEE Transactions on Speech and Audio Processing 13 2005 412 421
16. J. Droppo, A. Acero, and L. Deng Uncertainty decoding with splice for noise robust speech recognition Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 1 2002 pp. I-57-I-60
17. Y. Ephraim, and D. Malah Speech enhancement using a minimum-mean square error short-time spectral amplitude estimator IEEE Transactions on Acoustics Speech and Signal Processing 32 1984 1109 1121
18. Y. Ephraim, and D. Malah Speech enhancement using a minimum mean square error log-spectral amplitude estimator IEEE Transactions on Acoustics Speech and Signal Processing ASSP-33 1985 443 445
19. ETSI, January 2007. Speech Processing, Transmission and Quality Aspects (STQ); Distributed Speech Recognition; Front-end Feature Extraction Algorithm; Compression Algorithms, ETSI ES 202 050 v1.1.5 (2007-01).
20. Gales, M., 1996. Model-Based Techniques for Noise Robust Speech Recognition. Ph.D. Thesis. Cambridge University.
21. M.J.F. Gales, and P. Woodland Mean and variance adaptation within the MLLR framework Computer Speech and Language 10 1996 249 264
22. S. Gannot, and I. Cohen Speech enhancement based on the general transfer function GSC and postfiltering IEEE Transactions on Speech and Audio Processing 12 2004 561 571
23. L. Griffiths, and C. Jim An alternative approach to linearly constrained adaptive beamforming IEEE Transactions on Antennas and Propagation 30 1982 27 34
24. Habets, E.A.P., 2007. Single- and Multi-Microphone Speech Dereverberation using Spectral Enhancement. Ph.D. Thesis. Technische Universiteit Eindhoven.
25. R. Haeb-Umbach Uncertainty decoding and conditional Bayesian estimation Robust Speech Recognition of Uncertain or Missing Data - Theory and Applications 2011 Springer
26. V. Ion, and R. Haeb-Umbach Improved source modeling and predictive classification for channel robust speech recognition Proc. Interspeech 2006 633 636
27. D.H. Johnson, and D.E. Dudgeon Array Signal Processing: Concepts and Techniques 1993 Prentice Hall Englewood Cliffs
28. D. Kolossa, R.F. Astudillo, A. Abad, S. Zeiler, R. Saeidi, P. Mowlaee, J.P. Neto, and R. Martin CHIME challenge: approaches to robustness using beamforming and uncertainty-of-observation techniques International Workshop on Machine Listening in Multisource Environments (CHiME 2011) 2011 6 11
29. D. Kolossa, R.F. Astudillo, E. Hoffmann, and R. Orglmeister Independent component analysis and time-frequency masking for speech recognition in multi-talker conditions EURASIP Journal on Audio, Speech, and Music Processing 2010 2010
30. D. Kolossa, A. Klimas, and R. Orglmeister Separation and robust recognition of noisy, convolutive speech mixtures using time-frequency masking and missing data techniques Proc. Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) 2005 82 85
31. H. Liao, and M. Gales Issues with uncertainty decoding for noise robust automatic speech recognition Speech Communication 50 2008 265 277
32. R. McAulay, and M. Malpass Speech enhancement using a soft-decision noise suppression filter IEEE Transactions on Acoustics Speech and Signal Processing 28 1980 137 145
33. F. Nesta, and M. Matassoni Robust automatic speech recognition through on-line semi blind source extraction International Workshop on Machine Listening in Multisource Environments (CHiME 2011) 2011 18 23
34. A. Ozerov, M. Lagrange, and E. Vincent GMM-based classification from noisy features International Workshop on Machine Listening in Multisource Environments (CHiME 2011) Florence, Italy 2011
35. A. Vorwerk, S. Zeiler, D. Kolossa, R. Astudillo, and D. Lerch Use of missing and unreliable data for audiovisual speech recognition Robust Speech Recognition of Uncertain or Missing Data - Theory and Applications 2011 Springer
36. N. Yoma, and M. Villar Speaker verification in noise using a stochastic version of the weighted Viterbi algorithm IEEE Transactions on Speech and Audio Processing 10 3 2002 158 166
37. S. Young The HTK Book (for HTK Version 3.4) 2006 Cambridge University Engineering Department
38. D. Yu, L. Deng, J. Droppo, J. Wu, Y. Gong, and A. Acero Robust speech recognition using a cepstral minimum-mean-square-error-motivated noise suppressor IEEE Transactions on Audio, Speech, and Language Processing 16 2008 1061 1070
39. R. Zelinski A microphone array with adaptive post-filtering for noise reduction in reverberant rooms International Conference on Acoustics, Speech, and Signal Processing 1988 2578 2581